Question 1mediummultiple choice
Full question →mediummultiple choiceObjective-mapped
A logistics company receives real-time GPS tracking data from its delivery fleet via Azure Event Hubs. The data is a continuous stream of location updates (vehicle ID, latitude, longitude, timestamp). Additionally, the company has daily static route plan files in CSV format stored in Azure Data Lake Storage Gen2. The operations team needs to combine the live GPS stream with the route plans to create a near real-time dashboard showing if delivery vehicles are on schedule. They also want to run historical queries on both the stream data and route plans using T-SQL, without moving the data to another store. Which Azure service should they use as the primary analytics platform?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Best answer
Azure Synapse Analytics
Correct. Azure Synapse Analytics provides a unified platform for streaming ingestion (via pipelines), batch data in Data Lake, and T-SQL querying over both hot and cold data using serverless SQL pools. It supports near real-time dashboards and historical analysis.
B
Distractor review
Azure Stream Analytics
Incorrect. Azure Stream Analytics is designed for real-time stream processing only. It can output to sinks like Data Lake, but cannot directly query historical batch data or combine both in a single query for dashboards.
C
Distractor review
Azure Data Factory
Incorrect. Azure Data Factory is a data integration and orchestration service, not a query engine. It can move and transform data but cannot run ad-hoc T-SQL queries on the data lake for dashboards.
D
Distractor review
Azure Databricks
Incorrect. Azure Databricks is a powerful analytics platform based on Apache Spark, but its primary query language is Spark SQL (or Python/Scala), not T-SQL. It also requires more manual setup for streaming and batch integration compared to Synapse.
Common exam trap
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Technical deep dive
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Related practice questions
Related DP-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
Question 1
A data engineer needs to process streaming data from IoT devices and store the results in Azure Data Lake Storage for long-term analytics. The data must be processed in near real-time to detect anomalies and trigger alerts. Which Azure service should the engineer use for stream processing?
Question 2
A data engineer needs to query data stored in CSV files in Azure Data Lake Storage Gen2 using T-SQL in Azure Synapse Analytics, without loading the data into the database. Which feature should they use?
Question 3
A data engineer needs to process raw clickstream data from multiple websites that is stored in Azure Blob Storage as JSON files. The processing must run automatically every hour, transform the data into a structured format for reporting, and handle schema changes in the source data without manual intervention. Which Azure service should be used?
Question 4
A data engineer is designing a data lake architecture in Azure. They plan to first ingest raw data from various sources into a landing zone in Azure Data Lake Storage Gen2. Then they will clean, validate, and deduplicate that data in a second zone. Finally, they will create aggregated, business-ready datasets in a third zone for analysts. This layered approach is known as which architecture?
Question 5
A data engineer needs to transform large datasets stored in Azure Data Lake Storage Gen2 using Python and Apache Spark. They want a serverless compute option that automatically scales and requires no cluster management. Which Azure service should they use?
Question 6
A company collects customer feedback forms. Each form contains always-present fields like CustomerID and SubmissionDate, but also a free-text Comments field and optional fields like Rating or ProductCategory that vary between forms. How should this data be classified?
FAQ
Questions learners often ask
What does this DP-900 question test?
Static NAT maps one inside address to one outside address.
What is the correct answer to this question?
The correct answer is: Azure Synapse Analytics — Azure Synapse Analytics (formerly SQL Data Warehouse) is a limitless analytics service that brings together big data and data warehousing. It provides a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs. Synapse pipelines can ingest streaming data from Event Hubs and batch data from Data Lake Storage. Its SQL on-demand (serverless SQL pool) allows querying data directly in the data lake using T-SQL. The dedicated SQL pool provides MPP for high-performance analytics. This makes Synapse ideal for combining streaming and batch workloads with unified T-SQL querying. Azure Stream Analytics is only for real-time stream processing and cannot directly query historical batch data. Azure Data Factory is an orchestration service, not a query engine. Azure Databricks is a unified analytics platform, but it uses Spark SQL, not native T-SQL, and would require more custom coding.
What should I do if I get this DP-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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